4eme courbe
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83e4ccdd22
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24
plot/main.py
24
plot/main.py
@ -45,6 +45,20 @@ def delay(arr: list[tuple[int, np.ndarray]]) -> np.ndarray:
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nb += 1
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return delays
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def rb_available_distance(arr: list[tuple[int, np.ndarray]], distance) -> np.ndarray:
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available = np.zeros((size, 2))
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nb = 0
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for nb_users, data in arr:
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n = 0
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for x in data[:,6]:
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if int(x) == distance:
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n+=1
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available[nb, 0] = nb_users
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available[nb, 1] = n/ (200 * 10000) * 100
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nb += 1
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return available
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np_arr: list[tuple[int, np.ndarray]] = list()
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for i in nb_files:
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@ -52,6 +66,10 @@ for i in nb_files:
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averages = mean_mkn(np_arr)
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available = rb_available(np_arr)
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available_lp1 = rb_available_distance(np_arr, 200)
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available_lp2 = rb_available_distance(np_arr, 400)
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delays = delay(np_arr)
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delays.sort(axis=0)
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# Data for plotting
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@ -70,4 +88,10 @@ ax[1, 0].scatter(delays[:, 0], delays[:, 1])
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ax[1, 0].set(xlabel='number of users', ylabel='delays(ms)', title='Delay')
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ax[1, 0].grid()
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#ax[1, 1].scatter(available[:, 0], (available_lp1[:, 1]/available_lp2[:, 1])/available[:, 1] * 100)
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ax[1, 1].scatter(available[:, 0], available_lp1[:, 1])
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ax[1, 1].scatter(available[:, 0], available_lp2[:, 1])
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ax[1, 1].set(xlabel='number of users', ylabel='RB utilisés proche/loin/total', title='RB utilisés distance')
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ax[1, 1].grid()
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plt.show()
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